AI/ML Engineer

Job Summary

We are seeking an experienced MLOps GenAI Engineer with strong expertise in building and deploying production-grade ML pipelines, cloud-native solutions, and MLOps frameworks. The role requires a deep understanding of the ML lifecycle, CICD automation, containerization, and orchestration to deliver scalable, secure, and high-performing AIML solutions in enterprise environments.

Accountabilities

• Design, build, and deploy production-grade ML pipelines using modern frameworks and MLOps tools.
• Develop and manage CICD pipelines for ML model deployment and monitoring.
• Implement containerization (Docker) and orchestration (Kubernetes) for scalable model serving.
• Collaborate with data scientists, data engineers, and architects to productionize ML models.
• Ensure compliance with best practices for cloud-based ML deployments across AWS, Azure, or GCP.
• Integrate third-party services and APIs for enhanced solution capabilities.
• Contribute to architecture design while driving low-level implementation.
• Work closely with cross-functional teams across geographies to deliver end-to-end AIML solutions.

Essential Skills Experience

• Hands-on experience in Generative AI and MLOps.
• Strong proficiency in Python and ML frameworks such as TensorFlow, Keras, or PyTorch.
• Experience with MLOps tools: MLFlow, Kubeflow, Weights Biases, AWS SageMaker, Vertex AI, DVC, Airflow, Prefect.
• Proven experience in CICD pipelines, version control systems (Git), and deployment automation (Jenkins, Cloud Build, etc.).
• Strong knowledge of cloud platforms: AWS, GCP, Azure.
• Proficiency in containerization (Docker), Kubernetes, and Kafka.
• Strong background in statistical modeling, machine learning, and unstructured data analytics.
• Deep understanding of ML lifecycle and hands-on experience in productionizing ML models.
• Experience in data engineering pipelines.

Desirable Skills Experience

• Exposure to third-party integrations for AIML systems.
• Experience in architecture evolution for large-scale AIML solutions.
• Ability to work both independently and collaboratively in distributed teams.
• Strong problem-solving, stakeholder management, and technical communication skills.